fix(intern-decision-serve): register the checkpoint's inference module before executing it

Its dataclasses use postponed annotations and look their module up in sys.modules while the
class is built; importing by file path without registering it failed startup (closed).

services/intern-decision-serve/src/intern_decision_serve/engine.py

@@ -13,6 +13,7 @@ import hashlib
 import importlib.metadata
 import importlib.util
 import logging
+import sys
 import traceback
 from pathlib import Path
 from typing import Any
@@ -46,11 +47,21 @@ def _sha256(path: Path) -> str:
     return hashlib.sha256(path.read_bytes()).hexdigest()
 
 
+INFERENCE_MODULE = "intern_decision_inference"
+
+
 def _import_inference(path: Path):
-    """The checkpoint's own inference.py, imported by file path under a private module name."""
-    spec = importlib.util.spec_from_file_location("intern_decision_inference", path)
+    """The checkpoint's own inference.py, imported by file path under a private module name. It is
+    registered in sys.modules BEFORE it runs: its dataclasses (with `from __future__ import
+    annotations`) look their module up there while the class is being built."""
+    spec = importlib.util.spec_from_file_location(INFERENCE_MODULE, path)
     module = importlib.util.module_from_spec(spec)
-    spec.loader.exec_module(module)
+    sys.modules[INFERENCE_MODULE] = module
+    try:
+        spec.loader.exec_module(module)
+    except BaseException:
+        sys.modules.pop(INFERENCE_MODULE, None)
+        raise
     return module
 
 

services/intern-decision-serve/tests/test_engine.py

@@ -89,15 +89,17 @@ def reset_fake_torch():
 # A fake checkpoint: snapshots/<REVISION>/inference.py defining a DecisionEngine shaped like the real one.
 # ---------------------------------------------------------------------------------------------
 FAKE_INFERENCE = textwrap.dedent('''
+    from __future__ import annotations   # as in the real one: dataclasses then look the module up in sys.modules
     import json
+    from dataclasses import dataclass
     MODEL_NAME = "Intern-Decision-4B"
     EVENTS = []
     WARMUP_SHIFT = {"after_swap": 0.0}
     TOKEN_SKEW = {"n": 0}
 
+    @dataclass(frozen=True)          # the real inference.py defines one: needs sys.modules at exec time
     class Compiled:
-        def __init__(self, messages):
-            self.messages = messages
+        messages: list
 
     def validate_request(request):
         return {"state": request["state"], "questions": request["questions"]}